Yet if we consult Tol's paper--the very one cited by Nordhaus in support of the above quotation--we find that most economic studies find global warming will confer net benefits on humanity at least through the years 2050 - 2060. Only after we get at least another 2 degrees Celsius of warming (and that is compared to a recent baseline, not a preindustrial benchmark), do most studies in this literature say that the damages to certain parts of the world begin to overwhelm the benefits to other parts of the world.

As I mentioned in my IER post, I hope the average reader will agree with me that Nordhaus's summary of Tol's findings was extremely misleading (perhaps unintentionally). I daresay the average person, relying on mainstream media treatment of the issue, has been led to believe that "the consensus" of experts believes climate change is right now causing incredible damage and will only get worse as time passes.

And yet, the very person Nordhaus singled out as the leading scholar in the field, shows that the majority of the best available studies show global warming leading to net benefits at least for another four decades. (italics his)

Here's the new ground. It's on the difference between how the climate people and how economists think about confidence intervals. And it's a huge difference:

In a standard economic regression analysis, we typically approach things the way one is taught in high school when learning basic statistics. Namely, you set up a null hypothesis that is the opposite of the causal relationship you (the researcher) actually think exists. Then, if there is an apparent relationship in the data (such that you get a positive value on the coefficient for a certain term in a least-squares regression, say) you can see if the result holds up at a 90 percent, 95 percent, or 99 percent confidence interval.

In this normal context, the higher the confidence interval, it means the more confident you are that the apparent relationship between two measured variables isn't spurious. You are in effect saying, "If there really weren't any relationship between variable X and variable Y, then I wouldn't be getting this type of result 99 percent of the time. Therefore, I reject the null hypothesis--which says there is no relationship--and think that there really is a relationship."

Yet in charts of climate model projections, the "confidence interval" works the other way around. Here, the higher the number, the less confident we can be that an apparent match between the model and nature is due to the underlying accuracy of the model. To put it in other words, here the null hypothesis is that "this suite of climate models is accurately simulating global temperature." Thus if we make it harder to reject the null (by ramping up the confidence level), then it gives more wiggle room for the models.

Specifically, the "95% range" in the second graph above comes from looking at all of the observed "runs" of the suite of climate models, and then plotting the gray boundary that captures the realizations of 95% of the runs centered around the average. Ironically then, the less agreement there is between the individual climate models, then the wider the gray zone would be, and the harder it would be for Nature to "falsify" the suite of climate models. (italics his)

Comments and Sharing

While it is true that small amounts of warming can create net benefits, it is also true that small amounts of warming are already baked into the climate due to the lagged effects of past emissions. That is, even if we reduced emissions greatly starting now, we would expect a couple degrees of temperature rise just from the greenhouse gas we've already emitted. Further "business as usual" emissions would, as Nordhaus explains in great detail, push us into a regime where the net effects of further warming are negative. Nordhaus refers to this situation as a "sunk benefit".

In other words, it is a mistake (and a huge misreading of the literature) to assume that "warming over the next 40 years will produce net benefits" means the same thing as "continued emissions over the next 40 years will produce net benefits."

Murphy doesn't seem to understand how confidence intervals work. He seems to regard them as the complement of p-values or something. Whatever he's thinking, what he's saying is wrong. The confidence interval represents the range of values that (are believed to) have a specified probability of containing the actual value of the parameter. A very wide confidence interval indicates great uncertainty, and therefore a weaker claim about the value of the parameter. Conversely, a very narrow confidence interval indicates great certainty, and therefore a strong claim about the value of the parameter.

Naturally, a wide confidence interval is harder to "falsify" (I'll explain the quotes in a moment) than a narrow one because it makes a weaker claim. That is, while it takes only a small discrepancy with experiment to spoil a claim of near-certainty, any state of the world is consistent with the claim, "I don't know."

"Falsify" isn't even really the right word to use because posterior probability distributions (from which confidence intervals are derived) aren't hypotheses that are true or false; they are representations of belief, based on some set of measurements. When you add a new measurement to the set, you update your probability distribution (and therefore your confidence interval) to reflect the new information. If the new information is wildly inconsistent with your previous beliefs, the distribution will change a lot. On the other hand, if the new information is consistent with your previous beliefs, the distribution will get tighter (i.e., the confidence interval will shrink), indicating greater certainty.

The choice is effectively between a third less warming and a third less wealth a century hence.

It would be phenomenally irresponsible for us to choose the former for our progeny knowing as little as we really know about the consequences of warming. Almost certainly, our great-grandchildren will have more important things to worry about than how warm it is, and they will thank us for leaving them a wealthier, freer, and more technologically adept society to address them with.

None of this matters because the climate models are incorrect. The models wrongly assume that there is a carbon dioxide-related greenhouse gas warming effect for the planet. It just isn't so.

The greenhouse gas effect works within greenhouses only because of geometry. If the sun were straight overhead all day, then there would be no greenhouse gas effect. Increased CO2 in the greenhouse air would result in more solar photons warming the air, but every photon absorbed by the air is one less photon that would have warmed the plants, soil, racks, or floor of the greenhouse. The net solar energy and greenhouse temperatures would be the same for all CO2 levels.

In the real universe, the sun is not straight overhead all day. When shining at an angle (particularly in early morns and late afternoons), greenhouse gases (water and CO2) can be warmed by solar photons that normally would have passed through the greenhouse to strike and warm the surroundings. Increased CO2 in the greenhouse air causes more warming of the greenhouse and less warming of the area adjacent to the greenhouse that will receive less solar energy.

When the entire planet is the "greenhouse," there is no greenhouse gas effect. The mean planetary temperature is the same whether the solar photons warm air molecules, the land, or surface waters.

Few people are more dreary than climate alarmists. You have picked out just one of countless ways they have willfully distorted statistics.

I have always believed that it was impossible for climate alarmists to be correct. This does not mean I believe warming is impossible---anything is possible---but that it is virtually impossible for their science to be correct.

How many dubious assumptions, statements, monetary redistribution proposals, false statements of certainty, and self interested policy proposals does a group have to make before every possible Bayesian prior kicks in, screaming SCAM?

I will not list them all here (unless someone wants me to). Just needed to make the point.

You claim, "The choice is effectively between a third less warming and a third less wealth a century hence."

How could you possibly know that? This is an especially weird assertion coming from a climate skeptic as it requires that we assume we could reduce warming (and by 1/3) if we wanted to.

It also seems to assume that all the money spent on the problem would simply be subtracted from our total wealth rather than being used to employ people making investments that would produce additional power and efficiencies that would be enjoyed in the future.

For a guy who wants to emphasize how little we know about the effects of warming you sure do claim to know a lot about effects on wealth, freedom and technology 100 years from now.

@Mike Rulle

Your announcement of how firmly your mind is made up on this sits awkwardly with your lecturing others on their Bayesian priors.

They hypothesize several scenarios of future global development. A1 is roughly business as usual. B1 is more environmentally conscious.

The high growth scenario A1 predicts a per capita yearly GDP in 2100 of $80,000. The more environmentally conscious scenario B1 predicts that number to be $50,000. The expected warming for the latter is 1.8°C while for the former it is 2.8°C to 4.0°C depending on whether a low-carbon energy source is found to be as cheap as present-day high-carbon sources.

So we have to ask our descendants a century hence: Would you spend one third of your wealth per person per year to have a world that had experienced one third less warming?

It is hard to imagine their saying "Yes" without really really understanding the costs of that extra third of warming.

First, you bring up the point about sunk benefits as if David or I have brushed it under the rug. But there is literally a bold section header in my article titled "Tol Clarification—Global Warming’s “Sunk Benefits”" and Richard Tol himself says in the comments to the post, "Thanks for the clarification Robert." I'm not being sarcastic: Did you follow the link and read my article? If so, are you just complaining that David didn't carry through that point in his summary here?

Second, in light of your comment on the statistics, I realized perhaps I shouldn't have made it an issue of economists vs. climatologists. You have a mild point in that economists do confidence intervals around point estimates, where (of course) the higher the confidence, the wider the interval.

But I still say, that is not at all what the public thinks is going on here. We're *not* asking, "Assuming the climate models are correct, then with our observations of some realized variables, what is a 99% confidence interval around our estimate of the climate's sensitivity to CO2?"

No, instead we are asking, "Given the model's projections of temperature, compared to observed temperatures, how confident can we be that these models are any good?"

And in that context, for the guys at RealClimate to say, "Well, the observed temperatures are within the 99% confidence interval," is almost an irrelevant statement.

Let me put it this way: The Santer et al. people used a 95% confidence interval, while the RealClimate guys used a 99% one. If you asked the public which one is better, most would probably say the latter. But of course that's wrong; it's more reassuring if the actual temperatures fall within the 95% one.

Further, note again how what we are doing here is not at all analogous to coming up with an estimate of an unknown parameter. We *know* what the global temperature is. We're not trying to estimate it. So it's weird to put a confidence interval around it, looking back in time.

To reiterate what I said in the original article, I'm not accusing the climatologists of deception or stupidity. Given the nature of what they're trying to do, how else could you proceed? But my point is, we should all be aware of what it means when they say, "The actual temperatures of the last 5 years are within the 99% confidence interval, so the skeptics should shut up." That is a really odd statement once you spend time investigating what it really means.

You can argue the science of warming all you want but when you get into the area of the government doing something to counteract the warming you're entering the realm of religion. Thinking that government can put in place programs that will successfully manage something as complicated as the climate takes a huge leap of faith.

What will happen is the bureaucrats will channel money to their friends and empoverish the rest of us. Sorta like every other program they run.

"It is likely to be bad for my grandson but I shouldn't worry about that because I should assume that he 'will be far richer than we are now.'"

1) It won't even be bad for your grandson's generation, averaged over their lives (even if they are newborns, and have a life expectancy of 100 years). That's because, averaged over the entire century, global warming is likely to be a net benefit to them. (Based on Richard Tol's graph being correct, and global warming at staying at the rate of the last 5 decades, which is about 0.2 degrees Celsius per decade.)

2) Also, the "bad" effects are likely to be trivial...a couple percent of GDP in the year 2100, relative to what the GDP would be if there was no warming at all from 2000 to 2100. In other words, the GDP in 2101 with global warming will be what it would have been in 2100 without any global warming.

Thank you both - Bob Murphy and David Henderson - for some clarification on the "facts" floating around regards climate issues.

I'm not quite a climate change skeptic. I find the issue and the science interesting and compelling. Enough so that I believe it merits continued study.

But I am very much a government "solution" skeptic. It seems the government has one, all-purpose, posi-fit solution for every problem, real or imagined - inflict a wealth transfer on society. Invariably, the wealth transfer entails transferring wealth from society to government, right now.

You're correct that I was reacting to the portion of your article that David quoted. My apologies if the rest of the article treated the subject more fully. I'll try to get to it this weekend. I take it we're in agreement that the fact that you get net benefits over the next couple of degrees of warming isn't relevant to the question of mitigation. We're going to get that part of the warming not matter what we do.

If the question you're trying to answer is "How confident are we that the model's projections are correct?" then confidence intervals are simply the wrong tool for the task. If the real climate people are using confidence intervals in that way, then they're wrong.

On the other hand, when you say you want to know how likely it is that the model projections are "correct," what do you actually mean by that? If my model claims that there's a 99% chance that a future measurement will fall between X and Y, and the actual measurement comes in within that range, albeit near the edge, does that count as right or wrong? My claim would be that the model just needs to be updated to reflect the new data. Would you disagree with that?

I guess what you're saying (sorry, I'm kind of talking myself through your argument as I write this, and I don't have time to revise) is that once we make the updates for new data, you want to evaluate how we're doing over the entire corpus of old data. That seems like a reasonable thing to do, but when you do that you should make sure to evaluate the model against things it claims to predict. We know we can't predict high-frequency components of the temperature time series, and even decadal oscillations aren't well understood, so power at frequencies above that is noise from the model's perspective. When you take that into account, the models don't seem to be doing too badly.

Finally, if you want to claim that the models are just completely wrong, then what do you think is right instead? Presumably you're arguing that temperatures will level off or even decrease (otherwise there's nothing to argue about). That seems to me an extraordinary claim. Our understanding of atmospheric chemistry and radiative transfer is solid. For ocean uptake it's very good. The land carbon cycle is not very well understood, but ultimately it's reasonably well constrained by the requirement to match atmospheric CO2 concentrations. Really, the only mechanism that could offset the warming (which physics tells us we should see from greenhouse gas emissions) is enhanced cloud formation. Absent such an effect, increasing global mean temperatures seems like the obvious default presumption.

Now, certainly it's possible that you get enough negative feedback through that channel to offset all the forcing GHG emissions, plus the positive feedback from water vapor, but I'm puzzled by the people who seem convinced that it must be so, when there really hasn't been any evidence to suggest it.

(The last couple paragraphs seem a bit rambly, so let try to say it a little more concisely: Given what we know about chemistry and physics, does anybody seriously think we won't see increasing temperatures in the future? If not, then what are we really arguing about? If so, then what has them so convinced?)

I am an Aerospace Engineer and we frequently construct models of complex behavior and we frequently use confidence intervals in the same manner as the climate scientists. This is generally done to give an idea of how precise a model is.

Accuracy is measured by comparing observations to the predicted values. In this context precision refers to 'spread' of the distribution i.e. how large is the standard deviation. We would like models to be both precise and accurate but that may not be possible so then we go for accuracy and the best precision possible.

I think the important question is how large are the confidence intervals relative to the different scenarios. My doubts about the model result from my believing the confidence intervals are so large that it becomes difficult to compare differing models and scenarios since there is so much overlap. I may be wrong on this, since most of the models I deal with have much smaller confidence intervals and I may simple be projecting my expectations from AE into climate science where they are inappropriate.

It is possible to take the past and fit a curve to it that predicts anything you like about the future. So, how did models from the 1980s do in predicting the last quarter century? I have found it frustrating to find such data anywhere.

I think we should regard the climate and integrated assessment models as reasonably trustworthy until evidence suggests otherwise. Thus, we should regard the cost-benefit analyses that come out of those models as our best understanding of the likely consequences of various GHG abatement schemes (or lack thereof). That would suggest that the benefits (i.e., environmental damage costs avoided) for modest abatement (e.g. stabilization at 650ppm) exceed the costs, while the costs exceed the benefits for more stringent regimes.

We should probably also take into consideration the observation that the uncertainties on climate damages are mostly on the high side. With that in mind, there's a good argument that the optimal path (i.e., maximizes the expectation of Benefits - Costs) is to start with more abatement than you think you'll need and to relax the abatement scheme if it turns out not to be necessary (or, for that matter, if you find out that the warming models are wrong altogether). However, those calculations have so far been done only crudely (so far as I know), so it's hard to be more specific than that.

So, that's what I think we should believe. What we should do about those beliefs is more of a political question, and there is more room for reasonable people to differ.

I am sympathetic to the argument that even for the abatement targets for which the net present benefit is positive, it's pretty small, and therefore overwhelmed by intangible costs not captured in the analysis (e.g., the loss of liberty). I don't agree with it because I'm not persuaded that the intangible are that high, and I think our estimate of the likely damages from warming is probably a bit conservative. But I think it's a reasonable argument to make, especially if it feeds into a discussion of how to achieve stabilization targets while minimizing the intangible costs.

I can't say I really have a specific policy recommendation because I haven't really been studying the subject with an eye toward making that decision. (Mostly I'm looking for things like how costs are calculated and how you model decision making under uncertainty.) I suppose if someone put me on the spot and demanded I choose, I'd lean toward one of the moderate stabilization policies, but I try not to get too attached to any specific policy. I find that one's scientific objectivity is generally inversely proportional to one's propensity for activism.

While I'm on, I noticed that someone above came up with an estimate that abatement would cost 1/3 of GDP, based on a comparison of the SRES A1 and B1 scenarios. This is a terrible misunderstanding of what those scenarios represent. All of the SRES scenarios represent possible development paths in the absence of any emission abatement policy. Things like GDP and population in those scenarios are not outputs of some sort of model; they are prescriptions that define the scenarios. Those prescriptions are meant to be used as inputs to models, providing common sets of assumptions to use when comparing the results of one team's model run to another team's.

I'm a little surprised that that poster found such a difference in GDP between the two scenarios, since they are supposed to be similar in population and growth and differ mainly in GHG-intensity (with B1 scenarios having a larger proportion of service and information industries). Anyhow, wherever he's getting the numbers, he's using them incorrectly. Caveat lector, and all that.

I am well aware of what the SRES scenarios are and what they are used for, as evidenced by my saying "the IPCC SRES scenarios that IPCC forecasts are built on."

I'm a little surprised that that poster found such a difference in GDP between the two scenarios...

I didn't find that. The people who produced the IPCC SRES scenarios found that. Follow the link to see the numbers.

That it surprises you that a society that uses significantly more carbon-intensive energy is projected to be significantly more wealthy than one that doesn't is pretty telling.

Simply put, wealth increases exponentially. And while greenhouse gasses increase linearly with wealth, climate change due to them increases sublinearly. The bottom line is that only catastrophic nonlinear effects of global warming will cost significantly more than the benefit of maximizing exponential growth in the future.

But to your main point, I don't estimate that abatement would cost 1/3 of annual GDP. I simply note that IPCC projections of high carbon and low carbon alternative futures show a vast benefit from using carbon with not a vast decrease in warming.

As for actual proposed carbon abatement, I find that the net cost of the optimal policy of charging the social cost of atmospheric carbon, a la Nordhaus, is so close to the net cost of doing nothing that it is not worth giving governments the world over the power to regulate it.

Thank you for a well-stated response, even if it didn't quite answer my question.

Understand that my graduate degrees are in management and information systems, so I'm quite familiar with cost/benefit concepts, and have a sound working knowledge of research methods and statistical analysis. Hence my interest in the material in this post. (In an earlier life, I was a systems engineer [electrical], so I'm not terribly intimidated by the science.)

You (rightly) describe this work, and the scientific work as reflected in IPCC 4 and other studies as "our best understanding of the likely consequences of various GHG abatement schemes (or lack thereof)" - and I agree completely.

But the essence of the material discussed and presented in this post, and in IPCC 4 and other scientific materials I've read, indicate strongly that "our best understanding" isn't very good. I don't dis-believe it.

I merely have a much stronger (and reliable) belief that implementing any preemptive "stabilization" policy, when "our best understanding" isn't very good, is ill-fated and most probably detrimental.

Consider, for example, the policy of invading Iraq a few years ago - as a preemptive policy of precluding Hussein's use of WMDs, that "our best understanding" of the time indicated were an imminent threat. I believe that was an ill-fated and detrimental policy - both at the time and now.

My point being, I'm all in favor of improving the the state of "our best understanding". But I'm not supportive at all of taking known detrimental preemptive action now given the current state of "our best understanding".

Sorry, you're just wrong. None of the SRES scenarios are "projections" of anything. If you're interpreting them that way, then you're using them incorrectly.

You also seem to be using GDP directly as a proxy for wealth, which is a mistake, particularly for scenarios where a substantial portion of that economic activity is going to offset environmental damages.

Bottom line: don't try to use the SRES scenarios to make arguments about the cost of mitigation, and especially don't use the GDP figures from those scenarios. Use the cost benefit analyses.

Shayne,

You make a reasonable argument. The conclusion you come to is not the one I would come to, but there are a lot of considerations surrounding the treatment of risk for which there is no single right answer. I don't think, however, that the comparison to the Iraq war is apposite. The costs of an unnecessary war are way worse than the costs of an unnecessary mitigation policy.

Mark,

I don't have a specific answer to your question without doing a lot of digging that I don't have time to do right now. As you suggest, the costs are generally skewed toward the short-term, while the benefits are generally more in the long-term.

Discount rate is a very contentious subject, as illustrated by the debate that erupted over the Stern report. For what it's worth, in his response to the Stern report, Nordhaus makes a pretty compelling argument that the social discount rate and the utility function should be chosen to be consistent with observed real interest rates. If you do that, then it turns out you get pretty similar results no matter what social discount rate you use.

"The SRES report discusses emissions projections produced by a range of Integrated Assessment Models for a range of socio-economic storylines. Four `marker scenarios' are recommended as the basis of climate model projections, together with two further `illustrative scenarios':..."

Sorry, you're just wrong. None of the SRES scenarios are "projections" of anything.

You are kidding, right? They are not predictions, in that the producers don't want you to believe that is what will happen and that the results, being a century away, are extremely sensitive to unknown inputs. But they are certainly projections of alternate story lines.

...particularly for scenarios where a substantial portion of that economic activity is going to offset environmental damages.

The scenarios explicitly do not include effects of regulation of GHG or mitigation of GHG damages at all. To make the statement you made, you are assuming a conclusion.

Bottom line: don't try to use the SRES scenarios to make arguments about the cost of mitigation, and especially don't use the GDP figures from those scenarios. Use the cost benefit analyses.

That's a fair point, and why I also gave my opinion of the most persuasive cost-benefit analysis: that the (unconsidered) cost of giving government the power to tax and regulate carbon emission is not worth the extremely small benefit.

Now, certainly it's possible that you get enough negative feedback through that channel to offset all the forcing GHG emissions, plus the positive feedback from water vapor, but I'm puzzled by the people who seem convinced that it must be so, when there really hasn't been any evidence to suggest it.

My understanding is GHG emissions have an logarithmic effect and most of the effect has already occured. In order to get dramatic warming you have to have positive feedback from water vapor or something else. My question about positive feedback is it seems to be positive feedback from the warming, not GHG emissions. In which case any warming from any cause would have the same positive feedback and we would have had run-away warming long ago, say during the 1930's heat wave. Clearly there must be some kind of negative feedback which prevents this. Is the claim that the warming (not the emissions since they don't cause the positive feedback) is increasing so fast it will overwhelm whatever negative feedback has prevented run-away warming before? Is this a valid position given the temperature record the last decade? Am I missing something?

rpl: We know we can't predict high-frequency components of the temperature time series, and even decadal oscillations aren't well understood, so power at frequencies above that is noise from the model's perspective. When you take that into account, the models don't seem to be doing too badly.”

This is always one of the major issues about many alarmists. They know the chaotic nature of climate and even know the unpredictable behavior of decade temperature change, but soemhow they don’t truly believe it. They just think the chaos will vanish and the trend/signal will emerge in long term (say 30, 50, 100 years) if the noises are treated as white noise and can be averaged them out like IPCC models did. But, no, they can not be averaged out at least at scale of 10,000 years.

rpl: Finally, if you want to claim that the models are just completely wrong, then what do you think is right instead? Presumably you're arguing that temperatures will level off or even decrease (otherwise there's nothing to argue about). That seems to me an extraordinary claim.

This is your misunderstanding on statistics based hypothesis testing in which your goal is either accept or reject null hypothesis. If you claim temperature rised (null hypothesis), I test it and falsfy it, therefore I would reject your hypothesis temperature rised). Does it mean I support temperature dropped? No, it doesn’t mean that. (That is another null hypothesis that I may reject it too by testing it). What this means is I reject the null hypothesis of your study(or maybe your model).

Blogging software: Powered by Movable Type 4.2.1.
Pictures courtesy of the authors.
All opinions expressed on EconLog reflect those of the author or individual commenters, and do
not necessarily represent the views or positions of the Library of
Economics and Liberty (Econlib) website or its owner, Liberty Fund,
Inc.

The cuneiform inscription in the Liberty Fund logo is the
earliest-known written appearance of the word
"freedom" (amagi), or "liberty." It
is taken from a clay document written about 2300 B.C. in the Sumerian city-state of Lagash.